Interleaver optimization using population based metaheuristics

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dc.contributor.author Snášel, Václav
dc.contributor.author Platoš, Jan
dc.contributor.author Krömer, Pavel
dc.contributor.author Abraham, Ajith
dc.contributor.author Ouddane, Nabil
dc.contributor.author Húsek, Dušan
dc.date.accessioned 2011-01-07T08:19:13Z
dc.date.available 2011-01-07T08:19:13Z
dc.date.issued 2010
dc.identifier.citation Neural network world : international journal on non-standard computing and artificial intelligence. 2010, vol. 20, issue 5, p. 591-608. en
dc.identifier.issn 1210-0552
dc.identifier.uri http://hdl.handle.net/10084/83522
dc.description.abstract Since their appearance in 1993, first approaching the Shannon limit, turbo codes have given a new direction in the channel encoding field, especially since they have been adopted for multiple norms of telecommunications such as deeper communication. A robust interleaver can significantly contribute to the overall performance a turbo code system. Search for a good interleaver is a complex combinatorial optimization problem. In this paper, we present genetic algorithms and differential evolution, two bio-inspired approaches that have proven the ability to solve non-trivial combinatorial optimization tasks, as promising optimization methods to find a well-performing interleaver for large frame sizes. en
dc.language.iso en en
dc.publisher Akademie věd České republiky, Ústav informatiky en
dc.publisher České vysoké učení technické v Praze. Fakulta dopravní
dc.relation.ispartofseries Neural network world : international journal on non-standard computing and artificial intelligence en
dc.title Interleaver optimization using population based metaheuristics en
dc.type Article en
dc.identifier.location Není ve fondu ÚK en
dc.identifier.wos 000284915500002

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